Hidden turbulent motion that takes place inside the atmosphere of the Sun can be accurately predicted by a newly developed neural network.
Fed only temperature and vertical motion data collected from the surface of the solar photosphere, the AI model could correctly identify turbulent horizontal motion below the surface. This could help us to better understand solar convection, and processes that generate explosions and jets erupting from the Sun.
The solar photosphere is the region of the Sun's atmosphere that is commonly referred to as its surface. It's the lowest layer of the solar atmosphere, and the region in which solar activity such as sunspots, solar flares and coronal mass ejections originate. cells in the solar plasma. Hot plasma rises in the middle, and then falls back down around the edges as it moves outwards and cools.When we observe these cells, we can measure their temperature, as well as their motion via the Doppler effect, but horizontal motion can't be detected directly. However, smaller scale flows in these cells can interact with solar magnetic fields to trigger other solar phenomena.
This means that we could feed it solar data and expect that the results it returns are consistent with what is actually occurring on our fascinating, forbidding star.